Determination of the bearing from a geophone to a seismic source

ABSTRACT

Techniques are disclosed for determining the bearing from a three-axis geophone to a seismic source, such as a person or other man-made seismic source. In one embodiment, the techniques are implemented as a method that includes receiving outputs from a three-axis geophone (x axis, y axis and z axis outputs), computing a magnitude signal based on the x and y axis outputs, determining locations of each local peak in the magnitude signal, computing a bearing estimate for each peak, and computing a median of the bearing estimates. The resulting median bearing is an estimate of the bearing from the geophone to a target seismic source. In one such case, computing the magnitude signal based on the x and y axis outputs is performed in response to detecting the target seismic source in the phase-shifted z axis output.

STATEMENT OF GOVERNMENT INTEREST

The invention was made with United States Government support undercontract DAAE30-03-C-1094 awarded by the Army, and the United StatesGovernment has certain rights in this invention.

FIELD OF THE INVENTION

The invention relates to seismic sensor technology, and moreparticularly, determining the bearing from a three-axis geophone to aseismic source.

BACKGROUND OF THE INVENTION

A geophone is a known device that converts seismic energy (movement ordisplacement) to an electrical signal having a voltage that isproportional to the velocity of the seismic energy. They can be used,for example, to detect and quantify movement or displacement of theground (earthquakes) or machine vibrations. They can also be used in oilexploration and mining, where a man-made seismic stimulus is applied tothe earth, and a geophone is used to ‘read’ the reflection or responseto the seismic stimulus, which may indicate the presence of oil or aspecific mineral deposit (generally referred to as seismic surveying orprospecting).

U.S. Pat. No. 7,034,716, titled “Passive Real-Time VehicleClassification System Utilizing Unattended Ground Sensors” describes oneapplication of a geophone, for determining the type of a vehicletraversing terrain from acoustic and seismic noise emitted therefrom.

Although seismic energy is generally three-dimensional in nature, ageophone is typically configured to respond to single dimension.However, some applications require the full wave of seismic energy to bedetected, and in such cases, a multi-component geophone can be used,where individual geophones are deployed for each dimension of interest.For instance, a three-axis geophone detects seismic energy in threemutually orthogonal dimensions: x, y and z directions.

SUMMARY OF THE INVENTION

One embodiment of the present invention provides a method for computingthe bearing from a three-axis geophone to a seismic source. The methodincludes receiving outputs from a three-axis geophone, including x axis,y axis and z axis outputs, and computing a magnitude signal based on thex and y axis outputs. The method further includes determining locationsof each local peak in the magnitude signal, and computing a bearingestimate for each peak. The method further includes computing a medianof the bearing estimates, wherein the resulting median bearing is anestimate of the bearing from the geophone to a target seismic source. Inone particular such embodiment, the x axis, y axis and z axis outputsare analog, and receiving the outputs from a three-axis geophone furtherincludes digitizing each of the x, y, and z outputs. In anotherparticular such embodiment, computing a magnitude signal based on the xand y axis outputs is performed in response to first detecting thetarget seismic source in the z axis output. The method may includefiltering each of the x, y, and z outputs to remove noise. In one suchcase, the method includes phase shifting the filtered z axis output. Themethod may continue with projecting each filtered x and y axis outputonto the phase-shifted z axis output. The method may continue withapplying a moving average filter to each of the projected x and y axisoutputs. In one such case, computing a magnitude signal based on the xand y axis outputs includes computing the magnitude signal based on themoving average filtered x and y axis outputs, wherein computing amagnitude signal is performed in response to first detecting the targetseismic source in the phase-shifted z axis output.

Another embodiment of the present invention provides a machine readablemedium encoded with instructions that when executed by a processor,cause that processor to carry out a process for computing the bearingfrom a three-axis geophone to a seismic source. The process may include,for example, functionality similar to the methodology previouslydescribed.

Another embodiment of the present invention provides a system forcomputing the bearing from a three-axis geophone to a seismic source.The system includes a filter for receiving outputs from a three-axisgeophone, including x axis, y axis and z axis outputs, and filteringeach of the x, y, and z outputs to remove noise. The system furtherincludes a phase shifter for phase shifting the filtered z axis output,and a projector for projecting each filtered x and y axis output ontothe phase-shifted z axis output. The system further includes a movingaverage filter for filtering each of the projected x and y axis outputs,and a magnitude compute module for computing a magnitude signal based onthe moving average filtered x and y axis outputs. The system furtherincludes a peak finder for determining locations of each local peak inthe magnitude signal, and a bearing compute module for computing abearing estimate for each peak. The system further includes a bearingestimate compute module for computing a median of the bearing estimates,wherein the resulting median bearing is an estimate of the bearing fromthe geophone to a target seismic source. In one particular suchembodiment, the x axis, y axis and z axis outputs are analog, and thesystem further comprise an analog-to-digital converter for digitizingeach of the x, y, and z outputs. The system may further include adetector for detecting the target seismic source in the phase-shifted zaxis output, wherein in response to detecting a target seismic source inthe phase-shifted z axis output, the magnitude compute module is enabledto compute a magnitude signal based on the moving average filtered x andy axis outputs. In another particular such embodiment, the filter forfiltering each of the x, y, and z outputs to remove noise includes threea bandpass filter for each of the x, y, and z outputs.

The features and advantages described herein are not all-inclusive and,in particular, many additional features and advantages will be apparentto one of ordinary skill in the art in view of the drawings,specification, and claims. Moreover, it should be noted that thelanguage used in the specification has been principally selected forreadability and instructional purposes, and not to limit the scope ofthe inventive subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for computing the bearing from a three-axisgeophone to a seismic source, configured in accordance with anembodiment of the present invention.

FIG. 2 illustrates the filter and bearing computation module of thesystem shown in FIG. 1, configured in accordance with an embodiment ofthe present invention.

FIG. 3 illustrates a method for computing the bearing from a three-axisgeophone to a seismic source, in accordance with an embodiment of thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

Techniques are disclosed for determining the bearing from a three-axisgeophone to a seismic source, such as a person or other man-made seismicsource. As is known, the bearing to an object generally refers to thehorizontal angle between the direction of the object and that of truenorth, or even more generally, the direction to the object relative to agiven location.

The techniques can be used in conjunction with numerous types of seismicsensors that provide seismic activity data, and may be integrateddirectly into the housing of the sensor itself, or otherwise operativelycoupled to the sensor so as to receive the multidimensional outputs. Thetechniques can be implemented in hardware, software, or a combinationthereof.

Numerous applications will be apparent in light of this disclosure,including personnel detection and tracking. In any such cases, theability is provided to passively determine position information ofpersonnel or other seismic source using a low cost, low power sensor.

System Architecture

FIG. 1 illustrates a system for computing the bearing from a three-axisgeophone to a seismic source, configured in accordance with anembodiment of the present invention.

As can be seen, the system includes a three-axis geophone 103 having itsoutputs operatively coupled to an analog-to-digital converter (A/D) 104,which converts each of the analog outputs of the geophone 103 to itsdigital equivalent. These digital signals are then operatively coupledto filter 105, which is configured to filter out noisy areas of thegeophone frequency response. The filtered outputs of filter 105 areoperatively coupled to a bearing computation processor 107, whichcomputes the bearing of a seismic source 101. Although the system isshown in this example embodiment as being implemented with discretecomponents or modules, other embodiments may employ a degree ofintegration, where some or all of the functional modules are integrated,for instance, into a common housing or module.

The seismic source 101 can be any object or event of interest thatgenerates seismic energy, such as a person (e.g., walking, running, orotherwise moving), or a vehicle (e.g., moving vehicle or a stationaryvehicle such as tank that is actively firing rounds), or an explosion(e.g., discharge of large millimeter gun), or other such man-madeseismic source or event. Natural events, such as a tree falling ormudslide, may also provide seismic source 101. In general, such seismicsources provide unique seismic energy that can be identified.

The distance between the seismic source 101 and the system will varyfrom application to application. In some embodiments, that range isanywhere from several feet to several hundred miles, depending onfactors such as the sensitivity of the geophone 103, type of terrainthrough which the seismic energy must travel, and the seismic energygenerated by the source 101. For instance, seismic activity generated bya person will tend to have lower energy detectable within distances ofabout 1 mile or less, while seismic activity generated by an earthquakewill tend to have relatively higher energy detectable at distances of100 miles or more. Likewise, seismic energy will propagate different inwet soil based earth as compared to dry rock based earth. The techniquesdescribed herein can be employed in numerous such applications, and therange of operation can be set as desired.

The three-axis geophone 103 is this example embodiment is configured todetect seismic energy in the x-axis, the y-axis, and the z-axis, and canbe implemented with any commercially available or customized three-axisgeophones. Alternatively, the three-axis geophone 103 can be implementedwith three individual single-axis geophones that are configured tooperate together, so that each of the deployed single axis geophonesdetects seismic energy from a different axis. In one example embodiment,the geophone 103 is implemented using a Geospace GS-14L3 three-axisgeophone. In some such embodiments, accurate bearing angle computationscan be achieved at ranges up to 50 meters. Accuracy and range dependsprimarily on the local seismic environment surrounding the deployedgeophone and.

As will be appreciated, the accuracy, sensitivity and range of thegeophone will depend on factors such as the given application (e.g.,target seismic source and local seismic environment surrounding thegeophone), sources of interference (e.g., wind, vehicles, etc), and costconstraints (e.g., greater sensitivity and range typically comes atgreater cost). For example, personnel detection at a given range mayrequire a relatively higher sensitivity than heavy vehicle detection atthe same range. As sensitivity of seismic transducers improves, suchimproved transducers can equally be used in embodiments of the presentinvention.

The A/D converter 104 can be implemented with conventional technology.In one embodiment, the resolution of the A/D converter 104 is in therange of 8 to 32 bits, depending on the desired degree of sensitivityand accuracy. Filter 105 can generally be implemented with any filtertechnology that isolates the geophone output signals of interest. In oneexample embodiment, filter 105 is a bandpass filter configured toisolate the geophone output signals and to remove potential sources ofinterference, such as that arising from acoustical coupling andnon-targeted seismic sources within range of the geophone 103. Thefilter 105 can be coupled to the geophone by insulated wires or coaxialcable or other suitable conventional wired connections (e.g., fiberoptic cable or printed circuit board runs, etc). Alternatively, theconnection between filter 105 and geophone 103 can be implemented withconventional wireless technology, such as IEEE 802.11, Bluetooth,cellular or satellite based wireless links.

The bearing computation processor 107 receives the filtered outputs ofthe geophone 103, and operates to compute the bearing of seismic source101. The bearing computation processor 107, as well as filter 105, canbe implemented, for example, in any suitable programming language (e.g.,C, C++, object-oriented C, etc), and encoded on a machine readablemedium, that when executed by a processor, carries out the bearingcomputation. The processor may be included, for instance, in aconventional computer system, such as a desktop or laptop. Othersuitable processing environments can be used as well, such as a personaldigital assistant, smart phone, or any computing device havingsufficient memory and processing capability to execute the bearingcomputation processor 107 code. Other embodiments can be implemented,for instance, with gate-level logic or an application-specificintegrated circuit (ASIC) or chip set or other such purpose built logic,or a microcontroller having input/output capability (e.g., inputs forreceiving the x, y, and z outputs of the geophone) and a number ofembedded routines for carrying out the bearing computation. In short,filter 105 and module 107 can be implemented in hardware, software, or acombination thereof. The coupling between the filter 105 and module 107can be implemented, for example, with runs on a printed circuit board oroptical fiber. The previous discussion with reference to operativelycoupling the geophone 103 and the filter 105 is equally applicable here.

Filter and Bearing Computation Processor

FIG. 2 illustrates the filter 105 and bearing computation processor 107module of the system shown in FIG. 1, configured in accordance with anembodiment of the present invention.

As previously indicated, each of the filter 105 and bearing computationprocessor 107 can be implemented in hardware, software, or a combinationthereof. The block diagram of the example embodiment of FIG. 2 showsindividual functional modules to facilitate description andunderstanding, but other embodiments may integrate functionality of someor all modules into other modules, as will be apparent in light of thisdisclosure.

As can be seen, the bandpass filter 105 is implemented with a bandpassconfiguration, including bandpass filters 105 a, 105 b, and 105 c forfilter the digitized geophone x-axis, z-axis, and y-axis outputs,respectively. In one such embodiment, each geophone signal is filteredusing a bandpass filter having a passband ranging from about 10 Hz to 50Hz. In one such embodiment, each of bandpass filters 105 a, 105 b, and105 c is implemented with a 10 to 12 coefficient elliptical IIR filter.Other filter configurations can be used here, however, as long as thedesired passband and stopband regions are obeyed. In general, any filterdesign capable of highlighting or otherwise selectively passing theareas of the geophone's intrinsic frequency response and rejectingundesired noise. Numerous filter types and configurations will beapparent in light of this disclosure, and the present invention is notintended to be limited to any particular one filter or subset offilters. In any such cases, the filter 105 serves to clean the geophonesignals and remove sources of interference arising from, for example,acoustical coupling and other such undesired signals.

Module 203 performs a 90° degree phase shift on the vertical (z-axis)signal, which in one example embodiment is carried out using the Hilberttransform. Other suitable phase shift techniques can be employed aswell. Modules 201 a and 201 b operate to project the filtered x and yaxis signals, respectively, on to the phase-shifted z axis signalprovided by module 203. For instance, and in accordance with one exampleembodiment, assume H_z is the Hilbert transform of the bandpass filteredz-axis signal of the geophone 103. In addition, assume x is the bandpassfiltered x-axis signal of the geophone 103, and y is the bandpassfiltered y-axis signal of the geophone 103. In such an embodiment, theprojection of x onto z, (x_z) is obtained by pointwise multiplication ofH_z with x, where module 201 a is configured to implementx_z(t)=H_z(t)*x(t). Similarly, the projection of y onto z (y_z) isobtained by pointwise multiplication of H_z with y, where module 201 bis configured to implement y_z(t)=H_z(t)*y(t). Other such suitableprojection techniques may be employed.

The projected x and projected y signals output by modules 201 a and 201b are each smoothed using moving average filters 205 a and 205 b,respectively. In one specific embodiment, the moving average filters 205a and 205 b are each configured to compute an average over 3/16 of thesamples obtained in a 1 second frame (e.g., 192 samples for a signalsampled at 1024 Hz). The ratio of samples per sampling frequency can bedecreased or increased as desired, to suit particulars of a givenapplication including typical variations in the seismic signals receivedfrom the geophone 103 and the desired degree of smoothing. In general,the length of each filter 205 a and 205 b is dependent on the samplingrate used when collecting data samples from the geophone 103. Forexample, and in accordance with another example embodiment, the lengthof the filter is 96 samples for data sampled at 1024 Hz. In such a case,the filter values implemented by each of filter 205 a and 205 b are:h(t)=1/(2*96) for all t. Filter 205 a is applied to x_z(t) output bymodule 201 a to yield f_x(t), and filter 205 b is applied to y_z(t)output by module 201 b to yield f_y(t).

Target detector module 207 is configured to apply a detection algorithmto the phase-shifted z-axis signal. In one example embodiment, thetarget seismic source is a person, and the target detector module 207 isconfigured to carry out a kurtosis statistical analysis, such asdescribed in “Footstep Detection and Tracking” by Succi, Clapp, Gambert,and Prado (September 2001), which is herein incorporated by reference inits entirety. In general, as a person moves, seismic waves resultingfrom that person's footsteps propagate through the ground. The seismicwaves associated with movement of a person are different from otherseismic sources, such as those seismic waves associated with vehicles.For instance, one way to detect footsteps is to look for the periodicimpact of each step. The interval between impacts depends on the walker,but a typical interval is about 2 Hz. A distinguishing feature of afootstep when comparing time series data for footsteps to other seismicsignatures is the series of sharp spikes (as generated by a seismicsensor such as a geophone) resulting from each impact. This seismicpattern differs from other patterns induced, for example, by the windsover the ground and from vehicle noise. Vehicle noise, for instance, iscomposed of two parts: a periodic signature at the track impact rate anda broadband signature due to interaction with the random surfacefeatures on the ground. The shape of a footstep signature can bequantitatively distinguished from other seismic signatures, byconsidering a statistical measure of the amplitude of the signature, thekurtosis. Kurtosis is the ratio of the 4th to 2nd moment of theamplitude distribution of the signature. The kurtosis value compared fora sample sequence is much higher in the presence of impulsive eventsthan it is in the presence of Gaussian or sinusoidal signatures. Assuch, kurtosis statistical analysis of the seismic activity can be usedto detect a footstep (or other specific and seismically unique target),even in the presence of other diverse seismic sources. If another kindof man-made source was of interest, the target detector module 207 couldbe replaced by an appropriate detector for that type of source. In anycase, when the seismic source of interest in detected by target detectormodule 207, then module 207 can effectively enable the formation orcomputation of a magnitude signal as will now be explained.

The outputs of the x and y moving average filters 205 a and 205 b arecombined to form a magnitude signal by the magnitude compute module 209.This can be accomplished, for example, via a squared summation on asample-by-sample basis. For instance, and in accordance with one exampleembodiment, the compute module 209 is configured to compute themagnitude signal m(t) by taking the square root of the sum of f_x(t)squared plus f_y(t) squared, as demonstrated in the equation:m(t)=sqrt(f_x(t)²+f_y(t)²). As previously discussed, if the targetseismic source has not yet been detected (as indicated by module 207),then the magnitude computation can be disabled if so desired (e.g., toconserve processing power).

The magnitude signal output by module 209 is then provided to the peakfinder module 211, to determine peak locations in the magnitude signal.In one example embodiment, module 211 receives the magnitude signalm(t), which is then scanned in 4 second buffers to determine thelocations of any local peaks (local maxima) in the signal, which findssamples in the magnitude signal m(t) that are larger than both adjacentsamples. Numerous other buffer sizes for module 211 can be used as well,depending factors such as duration and type of seismic activity andsampling speed. Other suitable peak detectors can be used as well.

For each identified peak in a buffer, a bearing estimate is computed bymodule 213. In one embodiment, the module 213 is programmed or otherwiseconfigured to compute the arctangent of the ratio of the x-axis movingaverage output (as produced by module 205 a) to the y-axis movingaverage output (as produced by module 205 b). In more detail, beginningwith the largest peak in the magnitude signal m(t), module 213 computesthe arc tangent of f_y(t)/f_x(t) at the index corresponding to thatpeak. After zeroing out a window around the peak (whose size is chosenbased on the sampling rate of the geophone signal). In one example suchembodiment, the window size is 384 samples. This process is repeated forthe next remaining largest peak and again until all viable peaks havebeen processed.

The bearing estimates are then received by the module 215, which isconfigured to compute the median bearing estimate (i.e., the bearingestimate that statistically appears the most of all the estimatescomputed). In one example embodiment, module 215 is configured tocollect and sort the bearing estimates into angle order. This sortingprocess is complete, for instance, when the largest absolute angledifference between any two bearings has been minimized. The median ofthese sorted angles is then computed by module 215, thereby yielding thefinal bearing determination for that particular buffer of data. Forinstance, and in accordance with one example embodiment, module 215receives a list of peak bearings from module 213, and sorts the bearinglist in ascending order. Module 215 then finds the maximum angledifference (recognizing that no angle difference can be greater than 180degrees). Module 215 then reorders the list of bearings so that thefirst and last members have the largest difference, and then selects themedian bearing of that list. Module 215 can output that median bearing,which is the estimate of the bearing from the geophone 103 to theseismic source 101.

Methodology

FIG. 3 illustrates a method for computing the bearing from a three-axisgeophone to a seismic source, in accordance with an embodiment of thepresent invention. As previously explained, the method can beimplemented, for example, in any suitable programming language (e.g., C,C++, object-oriented C, etc), and encoded on a machine readable medium,that when executed by a processor, carries out the bearing computation.The processor may be included in any number of suitable processingenvironments having sufficient memory and processing capability toexecute the code. As previously indicated, each of the methodology canbe implemented in hardware, software, or a combination thereof. Theblock diagram of the example embodiment of FIG. 2 shows individualfunctional modules to facilitate description and understanding, butother embodiments may integrate functionality of some or all modulesinto other modules, as will be apparent in light of this disclosure.

The method includes digitizing and then filtering 301 outputs of 3-axisgeophone (x,y,z) to remove noise including potential interferencesources and other undesired signals. In some embodiments, the digitizingis carried out as described with reference to A/D converter 104, and thefiltering is carried out as described with reference to filter 105. Notethat in some embodiments, geophone may include an integrated A/Dconverter so that it three outputs are already digitized. In such cases,the outputs can be provided directly to filter 105.

The method continues with phase shifting 303 the filtered z axis output,and projecting 305 each filtered x and y axis output onto thephase-shifted z axis output. In some embodiments, the phase shifting iscarried out as described with reference to module 203, and theprojecting is carried out as described with reference to modules 201 aand 201 b.

The method continues with applying 307 a moving average filter to eachof the projected x and y axis outputs. In some embodiments, thisfiltering is carried out as described with reference to modules 205 aand 205 b. The method continues with detecting 309 target seismic sourcein the phase-shifted z axis output, and computing 311 a magnitude signalbased on the moving average filtered x and y axis outputs. In someembodiments, the detecting is carried out as described with reference tomodule 207, and the computing is carried out as described with referenceto module 209. Recall that is a target seismic source is not detected,then the filtering of 307 and/or computation of 311 may be disabled orotherwise held in abeyance until a target seismic source is detected at309.

The method continues with determining 313 the locations of each localpeak in the magnitude signal, and computing 315 a bearing estimate foreach peak. In some embodiments, the peak finding is carried out asdescribed with reference to module 211, and the bearing estimatecomputation is carried out as described with reference to module 213.The method continues with computing 317 a median of the bearingestimates, which in some embodiments, is carried out as described withreference to compute median bearing module 215. The resulting medianbearing is the estimate of the bearing from the geophone to a seismicsource (e.g., person).

The foregoing description of the embodiments of the invention has beenpresented for the purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdisclosed. Many modifications and variations are possible in light ofthis disclosure. It is intended that the scope of the invention belimited not by this detailed description, but rather by the claimsappended hereto.

1. A method for computing the bearing from a three-axis geophone to aseismic source, comprising: receiving outputs from a three-axisgeophone, including x axis, y axis and z axis outputs; computing amagnitude signal based on the x and y axis outputs; determininglocations of each local peak in the magnitude signal; computing abearing estimate for each peak; and computing a median of the bearingestimates, wherein the resulting median bearing is an estimate of thebearing from the geophone to a target seismic source.
 2. The method ofclaim 1 wherein the x axis, y axis and z axis outputs are analog, andreceiving the outputs from a three-axis geophone further includesdigitizing each of the x, y, and z outputs.
 3. The method of claim 1further comprising: filtering each of the x, y, and z outputs to removenoise.
 4. The method of claim 3 further comprising: phase shifting thefiltered z axis output.
 5. The method of claim 4 further comprising:projecting each filtered x and y axis output onto the phase-shifted zaxis output.
 6. The method of claim 5 further comprising: applying amoving average filter to each of the projected x and y axis outputs; 7.The method of claim 6 wherein computing a magnitude signal based on thex and y axis outputs comprises: computing the magnitude signal based onthe moving average filtered x and y axis outputs; wherein computing amagnitude signal is performed in response to first detecting the targetseismic source in the phase-shifted z axis output.
 8. The method ofclaim 1 wherein computing a magnitude signal based on the x and y axisoutputs is performed in response to first detecting the target seismicsource in the z axis output.
 9. A machine readable medium encoded withinstructions that when executed by a processor, cause that processor tocarry out a process for computing the bearing from a three-axis geophoneto a seismic source, the process comprising: receiving outputs from athree-axis geophone, including x axis, y axis and z axis outputs;computing a magnitude signal based on the x and y axis outputs;determining locations of each local peak in the magnitude signal;computing a bearing estimate for each peak; and computing a median ofthe bearing estimates, wherein the resulting median bearing is anestimate of the bearing from the geophone to a target seismic source.10. The machine readable medium of claim 9 wherein the received x axis,y axis and z axis outputs are digitized.
 11. The machine readable mediumof claim 9, the process further comprising: filtering each of the x, y,and z outputs to remove noise.
 12. The machine readable medium of claim11, the process further comprising: phase shifting the filtered z axisoutput.
 13. The machine readable medium of claim 12, the process furthercomprising: projecting each filtered x and y axis output onto thephase-shifted z axis output.
 14. The machine readable medium of claim13, the process further comprising: applying a moving average filter toeach of the projected x and y axis outputs;
 15. The machine readablemedium of claim 14 wherein computing a magnitude signal based on the xand y axis outputs comprises: computing the magnitude signal based onthe moving average filtered x and y axis outputs; wherein computing amagnitude signal is performed in response to first detecting the targetseismic source in the phase-shifted z axis output.
 16. The machinereadable medium of claim 9 wherein computing a magnitude signal based onthe x and y axis outputs is performed in response to detecting thetarget seismic source in the z axis output.
 17. A system for computingthe bearing from a three-axis geophone to a seismic source, comprising:a filter for receiving outputs from a three-axis geophone, including xaxis, y axis and z axis outputs, and filtering each of the x, y, and zoutputs to remove noise; a phase shifter for phase shifting the filteredz axis output; a projector for projecting each filtered x and y axisoutput onto the phase-shifted z axis output; a moving average filter forfiltering each of the projected x and y axis outputs; a magnitudecompute module for computing a magnitude signal based on the movingaverage filtered x and y axis outputs; a peak finder for determininglocations of each local peak in the magnitude signal; a bearing computemodule for computing a bearing estimate for each peak; and a bearingestimate compute module for computing a median of the bearing estimates,wherein the resulting median bearing is an estimate of the bearing fromthe geophone to a target seismic source.
 18. The system of claim 17wherein the x axis, y axis and z axis outputs are analog, and the systemfurther comprise an analog-to-digital converter for digitizing each ofthe x, y, and z outputs.
 19. The system of claim 17 further comprising:a detector for detecting the target seismic source in the phase-shiftedz axis output; wherein in response to detecting a target seismic sourcein the phase-shifted z axis output, the magnitude compute module isenabled to compute a magnitude signal based on the moving averagefiltered x and y axis outputs.
 20. The system of claim 17 wherein thefilter for filtering each of the x, y, and z outputs to remove noiseincludes three a bandpass filter for each of the x, y, and z outputs.